Precise Nutrition and Metabolic Syndrome, Remodeling the Microbiome with Polyphenols, Probiotics, and Postbiotics

Brizita, Djordjevic I.; Nevena, Ivanovic Dj

doi:10.1007/978-3-031-10153-3_6

Cited by 2 publications

(2 citation statements)

References 179 publications

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“…A study in an urban Korean population found that non-apartment residents were more likely to have MetS and related phenotypes compared to apartment residents in a model that was adjusted for confounding variables such as sociodemographic characteristics, residence area, health behavior, and nutritional information awareness [ 93 ]. Sanitary conditions are known to modify both environmental conditions and even intrinsic factors such as the gut microbiota, affecting the development of MetS [ 100 , 101 , 102 ]. All of these dimensions of social development are related in a non-trivial fashion to the development of the complex pathophenotypes making up metabolic syndrome as is further evidenced by our study.…”

Section: Discussionmentioning

confidence: 99%

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Gutiérrez-Esparza,

Martinez-Garcia,

Ramírez-delReal

et al. 2024

Nutrients

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This study investigated the relationship between Metabolic Syndrome (MetS), sleep disorders, the consumption of some nutrients, and social development factors, focusing on gender differences in an unbalanced dataset from a Mexico City cohort. We used data balancing techniques like SMOTE and ADASYN after employing machine learning models like random forest and RPART to predict MetS. Random forest excelled, achieving significant, balanced accuracy, indicating its robustness in predicting MetS and achieving a balanced accuracy of approximately 87%. Key predictors for men included body mass index and family history of gout, while waist circumference and glucose levels were most significant for women. In relation to diet, sleep quality, and social development, metabolic syndrome in men was associated with high lactose and carbohydrate intake, educational lag, living with a partner without marrying, and lack of durable goods, whereas in women, best predictors in these dimensions include protein, fructose, and cholesterol intake, copper metabolites, snoring, sobbing, drowsiness, sanitary adequacy, and anxiety. These findings underscore the need for personalized approaches in managing MetS and point to a promising direction for future research into the interplay between social factors, sleep disorders, and metabolic health, which mainly depend on nutrient consumption by region.

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Section: Discussionmentioning

confidence: 99%

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Gutiérrez-Esparza,

Martinez-Garcia,

Ramírez-delReal

et al. 2024

Nutrients

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“…There is a growing body of evidence supporting the efficacy of probiotics in the prevention and alleviation of obesity and related metabolic diseases [ 19 ]. Considering recent findings that one of the possible mechanisms of probiotic action is mediated by epigenetic influences, the aim of this study was to investigate the effect of a new probiotic concept on selected epigenetic markers specific to inflammatory and metabolic diseases.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic Aspects of a New Probiotic Concept—A Pilot Study

Okuka,

Schuh,

Krammer

et al. 2023

Life

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Several studies report the important role of an altered gut microbiota in the development of obesity, highlighting the potential use of probiotics in the treatment of obesity. The aim of this study is to investigate the effect of a novel probiotic approach on the expression of specific miRNAs and mRNAs associated with obesity in combination with the hypocholesterolemic octacosanol. Twenty overweight/obese women participated in a randomized, placebo-controlled, double-blind study and were randomly divided into two groups: the intervention group (daily one capsule containing Lactobacillus plantarum 299v (DSM9843), Saccharomyces cerevisiae var. boulardii, and 40 mg octacosanol; N = 12) and the placebo group (N = 8). Changes in lipid parameters and expression of miRNAs and mRNAs were assessed before (T0) and after the 12-week intervention (T1). After the intervention, the expression of miR-155-5p (9.38 ± 0.85 vs. 8.38 ± 1.06, p = 0.05) and miR-24-3p (3.42 ± 0.38 vs. 2.71 ± 0.97, p = 0.031) showed significant decreases in the intervention group when compared to the control group. At T1, the expression of miR-155-5p (8.69 ± 1.31 vs. 9.3 ± 0.85, p = 0.04), miR-125b-5p (5.41 ± 1.18 vs. 5.99 ± 1.36, p = 0.049), and TNF-α (10.24 ± 1.66 vs. 11.36 ± 1.12, p = 0.009) were significantly decreased in the intervention group. No changes in lipids and anthropometric parameters were observed. The novel probiotic approach had a positive effect on regulating the expression of certain miRNAs and mRNAs important for regulating inflammation and adipogenesis, which are essential for obesity onset and control.

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Precise Nutrition and Metabolic Syndrome, Remodeling the Microbiome with Polyphenols, Probiotics, and Postbiotics

Cited by 2 publications

References 179 publications

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Epigenetic Aspects of a New Probiotic Concept—A Pilot Study

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